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SAR: an algorithm for selecting a partition attribute in categorical-valued information system using soft set theory

Mat Deris, Mustafa and Mamat, Rabiei and Herawan, Tutut (2011) SAR: an algorithm for selecting a partition attribute in categorical-valued information system using soft set theory. International Journal of Information Retrieval Researchue, 1 (4). pp. 38-52. ISSN 2155-6377

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Abstract

Soft-set theory proposed by Molodstov is a general mathematic tool for dealing with uncertainty. Recently, several algorithms have been proposed for decision making using soft-set theory. However, these algorithms still concern on Boolean-valued information system. In this paper, Support Attribute Representative SAR, a soft-set based technique for decision making in categorical-valued information system is proposed. The proposed technique has been tested on three datasets to select the best partitioning attribute. Furthermore, two UCI benchmark datasets are used to elaborate the performance of the proposed technique in term of executing time. On these two datasets, it is shown that SAR outperforms three rough set-based techniques TR, MMR, and MDA up to 95% and 50%, respectively. The results of this research will provide useful information for decision makers to handle categorical datasets.

Item Type: Article
Uncontrolled Keywords: data mining; decision making; partition attribute selection; soft-set theory; support attribute representative SAR
Subjects: Q Science > QA Mathematics > QA273 Probabilities. Mathematical statistics
Divisions: Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User: Normajihan Abd. Rahman
Date Deposited: 23 Jan 2017 07:41
Last Modified: 23 Jan 2017 07:41
URI: http://eprints.uthm.edu.my/id/eprint/3624
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